What makes for effective, sustainable youth engagement in knowledge mobilization? A perspective for health services
Bibliographic record
Abstract
BACKGROUND: Young people who seek mental health treatment often also seek the services of non-profit organizations to support their well-being. Wisdom2Action (W2A) is a Canadian knowledge mobilization network that focuses on improving the mental health and well-being of children and youth in challenging contexts by increasing the use of evaluation, evidence and engagement in the youth-serving sector. Since 2013, W2A has engaged youth advisors (YAs) to provide input to W2A's Board, lead their own projects and co-design W2A activities. OBJECTIVE: In fall 2017, the YAs, as well as adult Board members and W2A staff, collaborated in a participatory evaluation to better understand the experiences and impacts of youth engagement. This article describes insights derived through this process. DESIGN AND PARTICIPANTS: Board, YAs and staff members participated in a reflective approach to informing, analysing and sharing the findings from this process. Individual interviews and review of documents, as well as iterative cycles of group analysis and synthesis, were conducted. RESULTS: Both YAC members and W2A benefit from YAs' leadership and engagement. The YAs position themselves as members of the youth-serving sector, not merely recipients of its services; as such, their professional development aligns with the mandates of W2A and merits further investment, despite challenges in impact measurement. CONCLUSION: This article identifies challenges and facilitators of implementing an effective and sustainable youth advisory council model of engagement in the context of a pan-Canadian network. The mutual gains and areas of growth for youth, adults and the organization described can inform health services, as well as funders and advocates for youth well-being.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.033 | 0.054 |
| Scholarly communication | 0.040 | 0.026 |
| Open science | 0.004 | 0.031 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".